Assessing probabilistic forecasts about particular situations

Abstract

How useful are probabilistic forecasts of the outcomes of particular situations? Potentially, they contain more information than unequivocal forecasts and, as they allow a more realistic representation of the relative likelihood of different outcomes, they might be more accurate and therefore more useful to decision makers. To test this proposition, I first compared a Squared-Error Skill Score (SESS) based on the Brier score with an Absolute-Error Skill Score (AESS), and found the latter more closely coincided with decision-makers’ interests. I then analysed data obtained in researching the problem of forecasting the decisions people make in conflict situations. In that research, participants were given lists of decisions that might be made and were asked to make a prediction either by choosing one of the decisions or by allocating percentages or relative frequencies to more than one of them. For this study I transformed the percentage and relative frequencies data into probabilistic forecasts. In most cases the participants chose a single decision. To obtain more data, I used a rule to derive probabilistic forecasts from structured analogies data, and transformed multiple singular forecasts for each combination of forecasting method and conflict into probabilistic forecasts. When compared using the AESS, probabilistic forecasts were not more skilful than unequivocal forecasts.